
| Problem Setting | Label Set | Target Data for Training | Post-Training on Target Labeled Data | ||
| Same for | Same between S&T Domains | Labeled Data | Unlabeled Data | ||
| Domain Adaptation [31, 32] | ✓ | ✓ | ✘ | ✓ | ✘ |
| Domain Adaptation with Category Shift [35, 2, 51] | ✓ | ✘ | ✘ | ✓ | ✘ |
| Multi-Source Domain Adaptation [55] | ✓ | ✓ | ✘ | ✓ | ✘ |
| Multi-Source Domain Adaptation with Category Shift [50] | ✘ | ✓ | ✘ | ✓ | ✘ |
| Domain Generalization [34] | ✓ | ✓ | ✘ | ✘ | ✘ |
| Heterogeneous Domain Generalization [30] | ✘ | ✘ | ✘ | ✘ | ✓ |
| The Proposed Open Domain Generalization | ✘ | ✘ | ✘ | ✘ | ✘ |
| 问题设定 | 标签集 | 训练目标数据 | 目标标注数据的后训练 | ||
| 科学与技术(S&T)领域之间相同 | 标注数据 | 未标注数据 | |||
| 领域自适应 [31, 32] | ✓ | ✓ | ✘ | ✓ | ✘ |
| 带有类别偏移的领域自适应 [35, 2, 51] | ✓ | ✘ | ✘ | ✓ | ✘ |
| 多源领域自适应 [55] | ✓ | ✓ | ✘ | ✓ | ✘ |
| 带有类别偏移的多源领域自适应 [50] | ✘ | ✓ | ✘ | ✓ | ✘ |
| 领域泛化 [34] | ✓ | ✓ | ✘ | ✘ | ✘ |
| 异构领域泛化 [30] | ✘ | ✘ | ✘ | ✘ | ✓ |
| 所提出的开放领域泛化 | ✘ | ✘ | ✘ | ✘ | ✘ |


| Art | Sketch | Photo | Cartoon | |||||||
| Acc | H-score | Acc | H-score | Acc | H-score | Acc | H-score | Acc | H-score | |
| AGG | 51.35 | 38.87 | 49.75 | 47.09 | 53.15 | 44.19 | 66.43 | 48.98 | ||
| MLDG [25] | 44.59 | 31.54 | 51.29 | 49.91 | 62.20 | 43.35 | 71.64 | 55.20 | ||
| FC [30] | 51.12 | 39.01 | 51.15 | 49.28 | 60.94 | 45.79 | 69.32 | 52.67 | ||
| Epi-FCR [27] | 54.16 | 41.16 | 46.35 | 46.14 | 70.03 | 48.38 | 72.00 | 58.19 | ||
| PAR [48] | 52.97 | 39.21 | 53.62 | 52.00 | 51.86 | 36.53 | 67.77 | 52.05 | ||
| RSC [21] | 50.47 | 38.43 | 50.17 | 44.59 | 67.53 | 49.82 | 67.51 | 47.35 | ||
| CuMix [33] | 53.85 | 38.67 | 37.70 | 28.71 | 65.67 | 49.28 | 74.16 | 47.53 | ||
| DAML (ours) | 54.10 | 43.02 | 58.50 | 56.73 | 75.69 | 53.29 | 73.65 | 54.47 | ||
| 艺术 | 素描 | 照片 | 卡通 | |||||||
| 准确率(Accuracy) | H分数 | 准确率(Accuracy) | H分数 | 准确率(Accuracy) | H分数 | 准确率(Accuracy) | H分数 | 准确率(Accuracy) | H分数 | |
| 聚合(Aggregation) | 51.35 | 38.87 | 49.75 | 47.09 | 53.15 | 44.19 | 66.43 | 48.98 | ||
| 元学习领域泛化(Meta-Learning Domain Generalization,MLDG) [25] | 44.59 | 31.54 | 51.29 | 49.91 | 62.20 | 43.35 | 71.64 | 55.20 | ||
| 特征对比(Feature Contrast,FC) [30] | 51.12 | 39.01 | 51.15 | 49.28 | 60.94 | 45.79 | 69.32 | 52.67 | ||
| 情景特征对比正则化(Episodic Feature Contrast Regularization,Epi - FCR) [27] | 54.16 | 41.16 | 46.35 | 46.14 | 70.03 | 48.38 | 72.00 | 58.19 | ||
| 渐进式对抗正则化(Progressive Adversarial Regularization,PAR) [48] | 52.97 | 39.21 | 53.62 | 52.00 | 51.86 | 36.53 | 67.77 | 52.05 | ||
| 随机风格组合(Random Style Composition,RSC) [21] | 50.47 | 38.43 | 50.17 | 44.59 | 67.53 | 49.82 | 67.51 | 47.35 | ||
| 类别混合(Class - wise Mixup,CuMix) [33] | 53.85 | 38.67 | 37.70 | 28.71 | 65.67 | 49.28 | 74.16 | 47.53 | ||
| 领域自适应元学习(Domain Adaptive Meta - Learning,DAML)(我们的方法) | 54.10 | 43.02 | 58.50 | 56.73 | 75.69 | 53.29 | 73.65 | 54.47 | ||
| Clipart | Real-World | Product | Art | |||||||
| Acc | H-score | Acc | H-score | Acc | H-score | Acc | H-score | Acc | H-score | |
| AGG | 42.83 | 44.98 | 62.40 | 53.67 | 54.27 | 50.11 | 42.22 | 40.87 | ||
| MLDG [25] | 41.82 | 41.26 | 62.98 | 55.84 | 56.89 | 52.25 | 42.58 | 40.97 | ||
| FC [30] | 41.80 | 41.65 | 63.79 | 55.16 | 54.41 | 52.02 | 44.13 | 43.25 | ||
| Epi-FCR [27] | 37.13 | 42.05 | 62.60 | 54.73 | 54.95 | 52.68 | 46.33 | 44.46 | ||
| PAR [48] | 41.27 | 41.77 | 65.98 | 57.60 | 55.37 | 54.13 | 42.40 | 42.62 | ||
| RSC [21] | 38.60 | 38.39 | 60.85 | 53.73 | 54.61 | 54.66 | 44.19 | 44.77 | ||
| CuMix [33] | 41.54 | 43.07 | 64.63 | 58.02 | 57.74 | 55.79 | 42.76 | 40.72 | ||
| DAML (ours) | 45.13 | 43.12 | 65.99 | 60.13 | 61.54 | 59.00 | 53.13 | 51.11 | ||
| 剪贴画 | 现实世界 | 产品 | 艺术 | |||||||
| 准确率(Accuracy) | H分数 | 准确率(Accuracy) | H分数 | 准确率(Accuracy) | H分数 | 准确率(Accuracy) | H分数 | 准确率(Accuracy) | H分数 | |
| 聚合(Aggregation) | 42.83 | 44.98 | 62.40 | 53.67 | 54.27 | 50.11 | 42.22 | 40.87 | ||
| 元学习领域泛化(Meta-Learning Domain Generalization,MLDG) [25] | 41.82 | 41.26 | 62.98 | 55.84 | 56.89 | 52.25 | 42.58 | 40.97 | ||
| 特征对比(Feature Contrast,FC) [30] | 41.80 | 41.65 | 63.79 | 55.16 | 54.41 | 52.02 | 44.13 | 43.25 | ||
| 流行病特征对比正则化(Epidemic Feature Contrast Regularization,Epi - FCR) [27] | 37.13 | 42.05 | 62.60 | 54.73 | 54.95 | 52.68 | 46.33 | 44.46 | ||
| 渐进式对抗正则化(Progressive Adversarial Regularization,PAR) [48] | 41.27 | 41.77 | 65.98 | 57.60 | 55.37 | 54.13 | 42.40 | 42.62 | ||
| 随机风格组合(Random Style Composition,RSC) [21] | 38.60 | 38.39 | 60.85 | 53.73 | 54.61 | 54.66 | 44.19 | 44.77 | ||
| 混合裁剪(CutMix with Uncertainty,CuMix) [33] | 41.54 | 43.07 | 64.63 | 58.02 | 57.74 | 55.79 | 42.76 | 40.72 | ||
| 领域自适应元学习(Domain Adaptive Meta - Learning,DAML)(我们的方法) | 45.13 | 43.12 | 65.99 | 60.13 | 61.54 | 59.00 | 53.13 | 51.11 | ||
| A | S | C | |||
| AGG | 77.6 | 70.3 | 94.4 | 73.9 | 79.1 |
| CIDDG [29] | 82.0 | 74.8 | 94.6 | 74.4 | 81.4 |
| MLDG [25] | 79.5 | 71.5 | 94.3 | 77.3 | 80.7 |
| CrossGrad [43] | 78.7 | 65.1 | 94.0 | 73.3 | 77.8 |
| MetaReg [1] | 79.5 | 72.2 | 94.3 | 75.4 | 80.4 |
| JiGen [3] | 79.4 | 71.4 | 96.0 | 75.3 | 80.4 |
| MASF [10] | 80.3 | 71.7 | 94.5 | 77.2 | 81.0 |
| Epi-FCR [27] | 82.1 | 73.0 | 93.9 | 77.0 | 81.5 |
| CSD [38] | 79.8 | 72.5 | 95.5 | 75.0 | 80.7 |
| DMG [5] | 76.9 | 75.2 | 93.4 | 80.4 | 81.5 |
| CuMix [33] | 82.3 | 72.6 | 95.1 | 76.5 | 81.6 |
| DAML | 83.0 | 74.1 | 95.6 | 78.1 | 82.7 |
| A | S | C | |||
| AGG | 77.6 | 70.3 | 94.4 | 73.9 | 79.1 |
| 因果不变分布域泛化(CIDDG) [29] | 82.0 | 74.8 | 94.6 | 74.4 | 81.4 |
| 元学习域泛化(MLDG) [25] | 79.5 | 71.5 | 94.3 | 77.3 | 80.7 |
| 交叉梯度(CrossGrad) [43] | 78.7 | 65.1 | 94.0 | 73.3 | 77.8 |
| 元正则化(MetaReg) [1] | 79.5 | 72.2 | 94.3 | 75.4 | 80.4 |
| 拼图生成(JiGen) [3] | 79.4 | 71.4 | 96.0 | 75.3 | 80.4 |
| 多尺度特征融合(MASF) [10] | 80.3 | 71.7 | 94.5 | 77.2 | 81.0 |
| 流行病特征对比正则化(Epi - FCR) [27] | 82.1 | 73.0 | 93.9 | 77.0 | 81.5 |
| 对比样本蒸馏(CSD) [38] | 79.8 | 72.5 | 95.5 | 75.0 | 80.7 |
| 动态元图(DMG) [5] | 76.9 | 75.2 | 93.4 | 80.4 | 81.5 |
| 混合裁剪(CuMix) [33] | 82.3 | 72.6 | 95.1 | 76.5 | 81.6 |
| 深度自适应元学习(DAML) | 83.0 | 74.1 | 95.6 | 78.1 | 82.7 |
| Clipart | Real | Painting | Sketch | |||||||
| Acc | H-score | Acc | H-score | Acc | H-score | Acc | H-score | Acc | H-score | |
| AGG | 29.78 | 34.06 | 65.33 | 64.72 | 44.30 | 51.04 | 27.59 | 35.41 | ||
| MLDG [25] | 29.66 | 35.11 | 65.37 | 54.40 | 44.04 | 50.53 | 26.83 | 34.57 | ||
| FC [30] | 29.91 | 35.42 | 64.77 | 63.65 | 44.13 | 50.07 | 28.56 | 34.10 | ||
| Epi-FCR [27] | 27.70 | 37.62 | 60.31 | 64.95 | 39.57 | 50.24 | 26.76 | 33.74 | ||
| PAR [48] | 29.29 | 39.99 | 64.09 | 62.59 | 42.36 | 46.37 | 30.21 | 39.96 | ||
| RSC [21] | 27.57 | 34.98 | 60.36 | 60.02 | 37.76 | 42.21 | 26.21 | 30.44 | ||
| CuMix [33] | 30.03 | 40.18 | 64.61 | 65.07 | 44.37 | 48.70 | 29.72 | 33.70 | ||
| DAML (ours) | 37.62 | 44.27 | 66.54 | 67.80 | 47.80 | 52.93 | 34.48 | 41.82 | ||
| 剪贴画 | 真实 | 绘画 | 素描 | |||||||
| 准确率(Acc) | H分数(H-score) | 准确率(Acc) | H分数(H-score) | 准确率(Acc) | H分数(H-score) | 准确率(Acc) | H分数(H-score) | 准确率(Acc) | H分数(H-score) | |
| 聚合(AGG) | 29.78 | 34.06 | 65.33 | 64.72 | 44.30 | 51.04 | 27.59 | 35.41 | ||
| 元学习领域泛化(MLDG [25]) | 29.66 | 35.11 | 65.37 | 54.40 | 44.04 | 50.53 | 26.83 | 34.57 | ||
| 特征对比(FC [30]) | 29.91 | 35.42 | 64.77 | 63.65 | 44.13 | 50.07 | 28.56 | 34.10 | ||
| 流行病特征对比正则化(Epi-FCR [27]) | 27.70 | 37.62 | 60.31 | 64.95 | 39.57 | 50.24 | 26.76 | 33.74 | ||
| 渐进式对抗正则化(PAR [48]) | 29.29 | 39.99 | 64.09 | 62.59 | 42.36 | 46.37 | 30.21 | 39.96 | ||
| 随机风格组合(RSC [21]) | 27.57 | 34.98 | 60.36 | 60.02 | 37.76 | 42.21 | 26.21 | 30.44 | ||
| 类别混合(CuMix [33]) | 30.03 | 40.18 | 64.61 | 65.07 | 44.37 | 48.70 | 29.72 | 33.70 | ||
| 领域自适应元学习(DAML (ours)) | 37.62 | 44.27 | 66.54 | 67.80 | 47.80 | 52.93 | 34.48 | 41.82 | ||

| w/ Meta | Cl | ||||||||
| - | - | - | - | ✓ | 42.2 | 64.8 | 57.6 | 49.6 | 53.6 |
| ✓ | - | - | - | ✓ | 43.8 | 64.9 | 57.1 | 51.7 | 54.4 |
| - | ✓ | - | - | ✓ | 43.8 | 65.7 | 58.2 | 52.4 | 55.0 |
| ✓ | ✓ | - | - | ✓ | 44.8 | 65.9 | 59.7 | 52.9 | 55.9 |
| ✓ | ✓ | - | ✓ | - | 44.1 | 65.1 | 59.7 | 52.2 | 55.3 |
| - | - | ✓ | ✓ | ✓ | 44.3 | 65.3 | 59.0 | 51.9 | 55.1 |
| ✓ | ✓ | - | ✓ | ✓ | 45.1 | 66.0 | 61.5 | 53.1 | 56.5 |
| 与Meta合作 | 氯(Cl) | ||||||||
| - | - | - | - | ✓ | 42.2 | 64.8 | 57.6 | 49.6 | 53.6 |
| ✓ | - | - | - | ✓ | 43.8 | 64.9 | 57.1 | 51.7 | 54.4 |
| - | ✓ | - | - | ✓ | 43.8 | 65.7 | 58.2 | 52.4 | 55.0 |
| ✓ | ✓ | - | - | ✓ | 44.8 | 65.9 | 59.7 | 52.9 | 55.9 |
| ✓ | ✓ | - | ✓ | - | 44.1 | 65.1 | 59.7 | 52.2 | 55.3 |
| - | - | ✓ | ✓ | ✓ | 44.3 | 65.3 | 59.0 | 51.9 | 55.1 |
| ✓ | ✓ | - | ✓ | ✓ | 45.1 | 66.0 | 61.5 | 53.1 | 56.5 |